Computational Modeling Of The Covid-19 Disease: Numerical Ode Analysis With R Programming

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Publisher : World Scientific
ISBN 13 : 9811222894
Total Pages : 109 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Computational Modeling Of The Covid-19 Disease: Numerical Ode Analysis With R Programming by : William E Schiesser

Download or read book Computational Modeling Of The Covid-19 Disease: Numerical Ode Analysis With R Programming written by William E Schiesser and published by World Scientific. This book was released on 2020-06-16 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is intended for readers who are interested in learning about the use of computer-based modelling of the COVID-19 disease. It provides a basic introduction to a five-ordinary differential equation (ODE) model by providing a complete statement of the model, including a detailed discussion of the ODEs, initial conditions and parameters, followed by a line-by-line explanation of a set of R routines (R is a quality, scientific programming system readily available from the Internet). The reader can access and execute these routines without having to first study numerical algorithms and computer coding (programming) and can perform numerical experimentation with the model on modest computers.

Computational Modeling of the COVID-19 Disease

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Publisher :
ISBN 13 : 9789811222887
Total Pages : 100 pages
Book Rating : 4.2/5 (228 download)

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Book Synopsis Computational Modeling of the COVID-19 Disease by : William E. Schiesser

Download or read book Computational Modeling of the COVID-19 Disease written by William E. Schiesser and published by . This book was released on 2020 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Numerical Modeling of COVID-19 Neurological Effects

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Author :
Publisher : CRC Press
ISBN 13 : 1000509982
Total Pages : 165 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Numerical Modeling of COVID-19 Neurological Effects by : William Schiesser

Download or read book Numerical Modeling of COVID-19 Neurological Effects written by William Schiesser and published by CRC Press. This book was released on 2021-12-27 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covid-19 is primarily a respiratory disease which results in impaired oxygenation of blood. The O2-deficient blood then moves through the body, and for the study in this book, the focus is on the blood flowing to the brain. The dynamics of blood flow along the brain capillaries and tissue is modeled as systems of ordinary and partial differential equations (ODE/PDEs). The ODE/PDE methodology is presented through a series of examples, 1. A basic one PDE model for O2 concentration in the brain capillary blood. 2. A two PDE model for O2 concentration in the brain capillary blood and in the brain tissue, with O2 transport across the blood brain barrier (BBB). 3. The two model extended to three PDEs to include the brain functional neuron cell density. Cognitive impairment could result from reduced neuron cell density in time and space (in the brain) that follows from lowered O2 concentration (hypoxia). The computer-based implementation of the example models is presented through routines coded (programmed) in R, a quality, open-source scientific computing system that is readily available from the Internet. Formal mathematics is minimized, e.g., no theorems and proofs. Rather, the presentation is through detailed examples that the reader/researcher/analyst can execute on modest computers. The PDE analysis is based on the method of lines (MOL), an established general algorithm for PDEs, implemented with finite differences. The routines are available from a download link so that the example models can be executed without having to first study numerical methods and computer coding. The routines can then be applied to variations and extensions of the blood/brain hypoxia models, such as changes in the ODE/PDE parameters (constants) and form of the model equations.

Covid-19 Unmasked: The News, The Science, And Common Sense

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Publisher : World Scientific
ISBN 13 : 9811233616
Total Pages : 408 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Covid-19 Unmasked: The News, The Science, And Common Sense by : Winfried Just

Download or read book Covid-19 Unmasked: The News, The Science, And Common Sense written by Winfried Just and published by World Scientific. This book was released on 2021-03-11 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can we keep up with the deluge of information about COVID-19 and tell which parts are most important and trustworthy?We read: 'Scientists recommend', 'Experts warn', 'A new model predicts'. How do scientific experts come up with their recommendations? What do their predictions really mean for us, for our friends, and our families?How can we make rational decisions? And how can we have sensible conversations about the pandemic when we disagree?These are the questions that this book is trying to address.It is written in the form of dialogues. Alice, a student of epidemiology, explains the science to three of her fellow students who have a lot of questions for her. The students have the same concerns that we all share to varying degrees: What the pandemic is doing to our health, our economy, and our cherished freedoms. In their conversations, they discover how the science relates to these questions.The book focuses on epidemiology, the science of how infections spread and how the spread can be mitigated. The science of how many infections can be prevented by certain kinds of actions. This is what we need to understand if we want to act wisely, as individuals and as a society.The author's goal is to help the reader think about the COVID-19 pandemic like an epidemiologist. About the various preventive measures, what they are trying to accomplish, what the obstacles are. About what is likely to be most effective in the long run at moderate economic and personal cost. About the likely consequences of personal decisions. About how to best protect oneself and others while allowing all of us to lead lives that are as close as possible to normal.While some chapters present slightly more advanced material than others, no scientific background is needed to follow the conversations. The technical concepts are explained in small steps and the occasional calculations in the book require only high-school mathematics.Related Link(s)

Computational Modeling and Data Analysis in COVID-19 Research

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Publisher : CRC Press
ISBN 13 : 1000384977
Total Pages : 271 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Computational Modeling and Data Analysis in COVID-19 Research by : Chhabi Rani Panigrahi

Download or read book Computational Modeling and Data Analysis in COVID-19 Research written by Chhabi Rani Panigrahi and published by CRC Press. This book was released on 2021-05-09 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book: Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19 Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreak Examines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19 Includes different case studies on COVID-19 Dr. Chhabi Rani Panigrahi is Assistant Professor in the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Bibudhendu Pati is Associate Professor and Head of the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Mamata Rath is Assistant Professor in the School of Management (Information Technology) at Birla Global University, Bhubaneswar, India. Prof. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia.

Computational Epidemiology

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Publisher : Springer Nature
ISBN 13 : 3030828905
Total Pages : 312 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Computational Epidemiology by : Ellen Kuhl

Download or read book Computational Epidemiology written by Ellen Kuhl and published by Springer Nature. This book was released on 2021-09-22 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19. It teaches the relevant tools to model and simulate nonlinear dynamic systems in view of a global pandemic that is acutely relevant to human health. If you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: This book is for you! It serves as a textbook for undergraduates and graduate students, and a monograph for researchers and scientists. It can be used in the mathematical life sciences suitable for courses in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming. This book is a personal reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it.

Mathematical Modeling Of Virus Infection: Ode/pde Analysis In R

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Publisher : World Scientific
ISBN 13 : 9811236658
Total Pages : 178 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Mathematical Modeling Of Virus Infection: Ode/pde Analysis In R by : William E Schiesser

Download or read book Mathematical Modeling Of Virus Infection: Ode/pde Analysis In R written by William E Schiesser and published by World Scientific. This book was released on 2021-03-17 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two models for the spread and control of a virus are detailed in this book: The Lung/Respiratory System Model (LSM) and the SVIR (Susceptible-Vaccinated-Infected-Recovered) Model.The LSM gives the spatiotemporal distribution of four viral-related proteins: virus population density along the lung air passage, host cell primary infection protein (viral genetic material (VGM)) concentration, host cell secondary infection protein (VGM) concentration, and air stream virion population density.The model is executed for a single inhalation, and a series of inhalation/exhalation cycles. For the latter, the progression of the viral infection into the lung is a principal result.The SVIR is first formulated as a system of ordinary differential equations (ODEs) in time, then extended to a system of PDEs to account for spatial effects (spatiotemporal modeling).Principal outputs from the ODE/PDE models are the levels of vaccinations and infections. For the latter, the efficacy of the vaccine is a parameter that can be varied in a computer-based analysis of a vaccine therapy.The coding of the models is in R, a quality, open-source scientific computing system, and can be executed on modest computers. The R routines are available from a download link so that the example models can be executed without having to first study numerical methods and computer coding. The routines can then be applied to variations and extensions of the ODE/PDE models, such as changes in the parameters and the form of the model equations.

Mathematical and Computational Modelling of Covid-19 Transmission

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Publisher : CRC Press
ISBN 13 : 1003807127
Total Pages : 337 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Mathematical and Computational Modelling of Covid-19 Transmission by : Mandeep Mittal

Download or read book Mathematical and Computational Modelling of Covid-19 Transmission written by Mandeep Mittal and published by CRC Press. This book was released on 2023-12-07 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Infectious diseases are leading threats and are of highest risk to the human population globally. Over the last two years, we saw the transmission of Covid-19. Millions of people died or were forced to live with a disability. Mathematical models are effective tools that enable analysis of relevant information, simulate the related process and evaluate beneficial results. They can help to make rational decisions to lead toward a healthy society. Formulation of mathematical models for a pollution-free environment is also very important for society. To determine the system which can be modelled, we need to formulate the basic context of the model underlying some necessary assumptions. This describes our beliefs in terms of the mathematical language of how the world functions. This book addresses issues during the Covid phase and post-Covid phase. It analyzes transmission, impact of coinfections, and vaccination as a control or to decrease the intensity of infection. It also talks about the violence and unemployment problems occurring during the post-Covid period. This book will help societal stakeholders to resume normality slowly and steadily.

Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis

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Publisher : Springer Nature
ISBN 13 : 3030797538
Total Pages : 416 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis by : Subhendu Kumar Pani

Download or read book Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis written by Subhendu Kumar Pani and published by Springer Nature. This book was released on 2021-12-13 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively covers the topic of COVID-19 and other pandemics and epidemics data analytics using computational modelling. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. The new era of pandemics and epidemics bring tremendous opportunities and challenges due to the plentiful and easily available medical data allowing for further analysis. The aim of pandemics and epidemics research is to ensure high-quality, efficient healthcare, better treatment and quality of life by efficiently analyzing the abundant medical, and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. In the past, it was a common requirement to have domain experts for developing models for biomedical or healthcare. However, recent advances in representation learning algorithms allow us to automatically learn the pattern and representation of the given data for the development of such models. Medical Image Mining, a novel research area (due to its large amount of medical images) are increasingly generated and stored digitally. These images are mainly in the form of: computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions related to health care. Image mining in medicine can help to uncover new relationships between data and reveal new and useful information that can be helpful for scientists and biomedical practitioners. Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis will play a vital role in improving human life in response to pandemics and epidemics. The state-of-the-art approaches for data mining-based medical and health related applications will be of great value to researchers and practitioners working in biomedical, health informatics, and artificial intelligence..

Computational Modeling of Infectious Disease

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Publisher : Elsevier
ISBN 13 : 0323958370
Total Pages : 478 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Computational Modeling of Infectious Disease by : Chris von Csefalvay

Download or read book Computational Modeling of Infectious Disease written by Chris von Csefalvay and published by Elsevier. This book was released on 2023-02-14 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Modeling of Infectious Disease: With Applications in Python provides an illustrated compendium of tools and tactics for analyzing infectious diseases using cutting-edge computational methods. From simple S(E)IR models, and through time series analysis and geospatial models, this book is both a guided tour through the computational analysis of infectious diseases and a quick-reference manual. Chapters are accompanied by extensive practical examples in Python, illustrating applications from start to finish. This book is designed for researchers and practicing infectious disease forecasters, modelers, data scientists, and those who wish to learn more about analysis of infectious disease processes in the real world. Connects computational infectious disease analysis to state-of-the-art data science Conveys ideas on epidemiology and infectious disease modeling in a clear, accessible way Provides code examples to elucidate best practices

Mathematical Modeling of Virus Infection

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Publisher :
ISBN 13 : 9789811236648
Total Pages : 178 pages
Book Rating : 4.2/5 (366 download)

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Book Synopsis Mathematical Modeling of Virus Infection by : William E. Schiesser

Download or read book Mathematical Modeling of Virus Infection written by William E. Schiesser and published by . This book was released on 1901 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Modelling and Imaging for SARS-CoV-2 and COVID-19

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Publisher : CRC Press
ISBN 13 : 9781003142584
Total Pages : 146 pages
Book Rating : 4.1/5 (425 download)

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Book Synopsis Computational Modelling and Imaging for SARS-CoV-2 and COVID-19 by : S. Prabha

Download or read book Computational Modelling and Imaging for SARS-CoV-2 and COVID-19 written by S. Prabha and published by CRC Press. This book was released on 2021-09 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2"--

Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact

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Publisher : Springer Nature
ISBN 13 : 981162450X
Total Pages : 635 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact by : Praveen Agarwal

Download or read book Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact written by Praveen Agarwal and published by Springer Nature. This book was released on 2021 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is a collection of selected research articles discussing the analysis of infectious diseases by using mathematical modelling in recent times. Divided into two parts, the book gives a general and country-wise analysis of Covid-19. Analytical and numerical techniques for virus models are presented along with the application of mathematical modelling in the analysis of their spreading rates and treatments. The book also includes applications of fractional differential equations as well as ordinary, partial and integrodifferential equations with optimization methods. Probability distribution and their bio-mathematical applications have also been studied. This book is a valuable resource for researchers, scholars, biomathematicians and medical experts.

Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation

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Publisher : Springer Nature
ISBN 13 : 9811941750
Total Pages : 63 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation by : Rahul Saxena

Download or read book Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation written by Rahul Saxena and published by Springer Nature. This book was released on 2022-09-02 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on mathematical modelling of COVID-19 pandemic using the Susceptible, Infectious, and Recovered (SIR) model. The predictive modelling of the disease, with the exact facts and figures, provides a ground to reason about growing trends and its future trajectory. The book emphasizes on how the pandemic actually spreads out, lockdown impact analysis, and future course of actions based on mathematical calculations. Moreover, since COVID-19 spread outburst has been twice, the intensity studies and comparative analysis of the two waves of COVID-19 are another interesting feature of the book content. The book is a knowledge base for various researchers and academicians to dive into the detailing of the COVID spread (mathematical) model and understand how it could be explored to draw outcomes. To represent the factual information and analytical results effectively, graphical and diagrammatic representations have been appended at appropriate places. To keep the explanation simple and yet concrete, mathematical concepts have also been introduced; to carry out analysis to generate results for understanding the viral dynamics.

Mathematical Analysis of Infectious Diseases

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Author :
Publisher : Academic Press
ISBN 13 : 0323904580
Total Pages : 346 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Mathematical Analysis of Infectious Diseases by : Praveen Agarwal

Download or read book Mathematical Analysis of Infectious Diseases written by Praveen Agarwal and published by Academic Press. This book was released on 2022-06-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Analysis of Infectious Diseases updates on the mathematical and epidemiological analysis of infectious diseases. Epidemic mathematical modeling and analysis is important, not only to understand disease progression, but also to provide predictions about the evolution of disease. One of the main focuses of the book is the transmission dynamics of the infectious diseases like COVID-19 and the intervention strategies. It also discusses optimal control strategies like vaccination and plasma transfusion and their potential effectiveness on infections using compartmental and mathematical models in epidemiology like SI, SIR, SICA, and SEIR. The book also covers topics like: biodynamic hypothesis and its application for the mathematical modeling of biological growth and the analysis of infectious diseases, mathematical modeling and analysis of diagnosis rate effects and prediction of viruses, data-driven graphical analysis of epidemic trends, dynamic simulation and scenario analysis of the spread of diseases, and the systematic review of the mathematical modeling of infectious disease like coronaviruses. Offers analytical and numerical techniques for virus models Discusses mathematical modeling and its applications in treating infectious diseases or analyzing their spreading rates Covers the application of differential equations for analyzing disease problems Examines probability distribution and bio-mathematical applications

Mathematical Modeling Approach To Infectious Diseases, A: Cross Diffusion Pde Models For Epidemiology

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Author :
Publisher : World Scientific
ISBN 13 : 9813238801
Total Pages : 460 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Mathematical Modeling Approach To Infectious Diseases, A: Cross Diffusion Pde Models For Epidemiology by : Schiesser William E

Download or read book Mathematical Modeling Approach To Infectious Diseases, A: Cross Diffusion Pde Models For Epidemiology written by Schiesser William E and published by World Scientific. This book was released on 2018-06-27 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Mathematics

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Publisher : CRC Press
ISBN 13 : 1000889432
Total Pages : 529 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Computational Mathematics by : Dimitrios Mitsotakis

Download or read book Computational Mathematics written by Dimitrios Mitsotakis and published by CRC Press. This book was released on 2023-06-19 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject, as well as advantages and pitfalls of classical numerical methods alongside with computer code and experiments in Python. Each chapter closes with modern applications in physics, engineering, and computer science. Features: No previous experience in Python is required. Includes simplified computer code for fast-paced learning and transferable skills development. Includes practical problems ideal for project assignments and distance learning. Presents both intuitive and rigorous faces of modern scientific computing. Provides an introduction to neural networks and machine learning.